An Energy Optimization Clustering Scheme for Multi-Hop Underwater Acoustic Cooperative Sensor Networks

Abstract

In this paper, we propose an improved energy optimization clustering algorithm (EOCA) for the multi-hop underwater acoustic cooperative sensor networks (UWA-CSN) due to the limited energy supply of the underwater sensor nodes. The proposed EOCA scheme considers multiple factors, such as the number of neighbor nodes, the residual energy of each node, the motion of the sensor nodes caused by the ocean currents, and the distance between the sink node and each underwater sensor node. All these factors are considered within the framework of the multi-hop cooperative communication. Moreover, in the proposed energy optimization scheme, we define a residual energy based maximum effective communication range (reE-MECR) according to the residual energy of each underwater sensor node, which can adaptively control the energy consumption of data transmission for each hop. Compared with the existing clustering scheme, the experimental results demonstrate that the proposed EOCA scheme can not only prolong the life time of the multi-hop UWA-CSN, but also keep a good communication and networking performance, including the package delivery ratio, the energy consumption efficiency, and the network coverage area. The proposed scheme can obtain both the clustering benefit and the cooperative communication benefit for the multi-hop UWA-SN in terms of energy saving in underwater environments. INDEX TERMS Underwater acoustic networks, cooperative communications, clustering algorithm, energy optimization.

A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks

“…For the convenience of comparison, the proposed algorithm in this paper is called ant colony optimization clustering routing (ACOCR). Five existing popular algorithms: LEACH [18], DUCS [19], LEACH-ANT [47], CUWSN [23], and EOCA [11] were chosen as the references to validate the proposed algorithm according to the number of surviving nodes, the energy consumption of the network, and the packet loss ratio. MATLAB was used to carry out the simulation where sensor nodes were randomly placed in a 3D area of 5000 m × 5000 m × 1000 m and the coordinate of the SN was (2500, 2500, 0).…”

“…In conserving energy, multi-hop data transmission in long-distance communication for UWSNs is more effective than single-hop transmission [10]. Additionally, to alleviate the problems of data collision and traffic load balance, it is important to design a reliable network topology [11]. Many studies have shown that the clustering routing algorithm is capable of saving energy, avoiding collisions, and balancing traffic load because it employs the clustering topology and uses a multi-hop mechanism during the inter-cluster data transmission [12,13].…”

“…The cluster sleep-wake scheduling algorithm in UWSNs was proposed by Zhang et al in [30], which shows the rotating temporary control nodes that control the sleep-wake scheduling, thus minimizing the energy dissipation. The energy optimization clustering algorithm (EOCA) was put forward by Yu et al in [11], where the number of neighboring nodes, the remaining energy of nodes, the motion of nodes, and the distance factor are taken into account. Additionally, the EOCA provides a maximum effective communication range based on the remaining energy of nodes, thereby controlling the energy dissipation for packet delivery.…”

Node Energy Consumption Balanced Multi-Hop Transmission for Underwater Acoustic Sensor Networks Based on Clustering Algorithm

“…It has been demonstrated that protocols based on clusters are viable with respect to sparing energy [1]. However, since long-distance communications will cause higher energy consumption than short-distance communications, applying multi-hop transmissions among cluster heads to convey data can further reduce the energy consumption of the network [24].…”

Underwater Wireless Sensor Networks: An Energy-Efficient Clustering Routing Protocol Based on Data Fusion and Genetic Algorithms

“…Underwater wireless sensor networks (UWSNs) consist of many underwater wireless sensor nodes distributed within the marine environment, which support a wide variety of applications such as surveillance, navigation, data acquisition, resource exploration, and disaster prevention [1][2][3]. Each sensor node of UWSNs is equipped with an acoustic modem because it uses acoustic signals to communicate with each other [4]. These nodes are capable of forming a network without any infrastructure.…”